gFdZddlZddlmZmZmZer ddlmZddlm Z e j e Z GddeZ Gd d eZGd d eZgd ZdS)zALIGN model configurationN) TYPE_CHECKINGListUnion)PretrainedConfig)loggingceZdZdZdZ dfd Zedeee j fddfdZ xZ S)AlignTextConfigal This is the configuration class to store the configuration of a [`AlignTextModel`]. It is used to instantiate a ALIGN text encoder according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of the text encoder of the ALIGN [kakaobrain/align-base](https://huggingface.co/kakaobrain/align-base) architecture. The default values here are copied from BERT. Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information. Args: vocab_size (`int`, *optional*, defaults to 30522): Vocabulary size of the Align Text model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`AlignTextModel`]. hidden_size (`int`, *optional*, defaults to 768): Dimensionality of the encoder layers and the pooler layer. num_hidden_layers (`int`, *optional*, defaults to 12): Number of hidden layers in the Transformer encoder. num_attention_heads (`int`, *optional*, defaults to 12): Number of attention heads for each attention layer in the Transformer encoder. intermediate_size (`int`, *optional*, defaults to 3072): Dimensionality of the "intermediate" (often named feed-forward) layer in the Transformer encoder. hidden_act (`str` or `Callable`, *optional*, defaults to `"gelu"`): The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`, `"relu"`, `"silu"` and `"gelu_new"` are supported. hidden_dropout_prob (`float`, *optional*, defaults to 0.1): The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. attention_probs_dropout_prob (`float`, *optional*, defaults to 0.1): The dropout ratio for the attention probabilities. max_position_embeddings (`int`, *optional*, defaults to 512): The maximum sequence length that this model might ever be used with. Typically set this to something large just in case (e.g., 512 or 1024 or 2048). type_vocab_size (`int`, *optional*, defaults to 2): The vocabulary size of the `token_type_ids` passed when calling [`AlignTextModel`]. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. layer_norm_eps (`float`, *optional*, defaults to 1e-12): The epsilon used by the layer normalization layers. pad_token_id (`int`, *optional*, defaults to 0): Padding token id. position_embedding_type (`str`, *optional*, defaults to `"absolute"`): Type of position embedding. Choose one of `"absolute"`, `"relative_key"`, `"relative_key_query"`. For positional embeddings use `"absolute"`. For more information on `"relative_key"`, please refer to [Self-Attention with Relative Position Representations (Shaw et al.)](https://arxiv.org/abs/1803.02155). For more information on `"relative_key_query"`, please refer to *Method 4* in [Improve Transformer Models with Better Relative Position Embeddings (Huang et al.)](https://arxiv.org/abs/2009.13658). use_cache (`bool`, *optional*, defaults to `True`): Whether or not the model should return the last key/values attentions (not used by all models). Only relevant if `config.is_decoder=True`. Example: ```python >>> from transformers import AlignTextConfig, AlignTextModel >>> # Initializing a AlignTextConfig with kakaobrain/align-base style configuration >>> configuration = AlignTextConfig() >>> # Initializing a AlignTextModel (with random weights) from the kakaobrain/align-base style configuration >>> model = AlignTextModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```align_text_model:w gelu皙?{Gz?-q=rabsoluteTc tjdi|||_||_||_||_||_||_||_||_ | |_ | |_ | |_ | |_ ||_||_| |_dS)N)super__init__ vocab_size hidden_sizenum_hidden_layersnum_attention_heads hidden_actintermediate_sizehidden_dropout_probattention_probs_dropout_probmax_position_embeddingstype_vocab_sizeinitializer_rangelayer_norm_epsposition_embedding_type use_cache pad_token_id)selfrrrrr rr!r"r#r$r%r&r)r'r(kwargs __class__s i/var/www/html/ai-engine/env/lib/python3.11/site-packages/transformers/models/align/configuration_align.pyrzAlignTextConfig.__init__cs& ""6"""$&!2#6 $!2#6 ,H)'>$.!2,'>$"(pretrained_model_name_or_pathreturnrc N|||j|fi|\}}|ddkr|d}d|vrMt|dr=|d|jkr,t d|dd|jd|j|fi|S)N model_typealign text_configYou are using a model of type to instantiate a model of type N. This is not supported for all configurations of models and can yield errors._set_token_in_kwargsget_config_dictgethasattrr2loggerwarning from_dictclsr/r+ config_dicts r-from_pretrainedzAlignTextConfig.from_pretraineds   (((1c12OZZSYZZ V ??< ( (G 3 3%m4K ; & &73 +E+E &+VbJcgjguJuJu NNr\1Jrr>rrr    s}[33F333r.)r r rrrrrrrrrrrrT) __name__ __module__ __qualname____doc__r2r classmethodrstrosPathLikerC __classcell__r,s@r-r r s? ? B$J%( # *!#)#)#)#)#)#)J4E#r{BR